Transformation of particle swarm optimization algorithm

Abstract

Abstract: The functions of inertance part, individual perception part and population perception part about the particle swarm optimization algorithm are analysed. Every part of the iterative equations about the particle swarm optimization algorithm is transformed. Three new particle swarm optimization algorithms are obtained. The three new algorithms possess preferable optimization abilities which are illustrated by examples.

Key words: particle swarm optimization algorithm, transformation formula, optimization

摘要： 分析了粒子群算法的惯性部分、个体认知部分和群体认知部分的作用，对粒子群算法迭代方程的各部分进行变形，获得了三种新形式的粒子群算法。用算例说明所得到的三个新的粒子群算法具有较好的优化能力。

关键词: 粒子群优化算法, 公式变形, 最优化

YUAN Dailin. Transformation of particle swarm optimization algorithm[J]. Computer Engineering and Applications, 2015, 51(5): 23-26.

袁代林. 粒子群优化算法的变形[J]. 计算机工程与应用, 2015, 51(5): 23-26.

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Transformation of particle swarm optimization algorithm

粒子群优化算法的变形

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